Pandas Profiling Report

Dataset statistics

Number of variables	23
Number of observations	58919
Missing cells	0
Missing cells (%)	0.0%
Duplicate rows	0
Duplicate rows (%)	0.0%
Total size in memory	10.3 MiB
Average record size in memory	184.0 B

Variable types

Numeric	16
Categorical	7

Alerts

`in_transit_qty` is highly correlated with `forecast_6_month` and 6 other fields	High correlation
`forecast_3_month` is highly correlated with `forecast_6_month` and 5 other fields	High correlation
`forecast_6_month` is highly correlated with `in_transit_qty` and 6 other fields	High correlation
`forecast_9_month` is highly correlated with `in_transit_qty` and 6 other fields	High correlation
`sales_1_month` is highly correlated with `in_transit_qty` and 7 other fields	High correlation
`sales_3_month` is highly correlated with `in_transit_qty` and 7 other fields	High correlation
`sales_6_month` is highly correlated with `in_transit_qty` and 7 other fields	High correlation
`sales_9_month` is highly correlated with `in_transit_qty` and 7 other fields	High correlation
`min_bank` is highly correlated with `in_transit_qty` and 4 other fields	High correlation
`perf_6_month_avg` is highly correlated with `perf_12_month_avg`	High correlation
`perf_12_month_avg` is highly correlated with `perf_6_month_avg`	High correlation
`in_transit_qty` is highly correlated with `forecast_3_month` and 7 other fields	High correlation
`forecast_3_month` is highly correlated with `in_transit_qty` and 7 other fields	High correlation
`forecast_6_month` is highly correlated with `in_transit_qty` and 7 other fields	High correlation
`forecast_9_month` is highly correlated with `in_transit_qty` and 7 other fields	High correlation
`sales_1_month` is highly correlated with `in_transit_qty` and 7 other fields	High correlation
`sales_3_month` is highly correlated with `in_transit_qty` and 7 other fields	High correlation
`sales_6_month` is highly correlated with `in_transit_qty` and 7 other fields	High correlation
`sales_9_month` is highly correlated with `in_transit_qty` and 7 other fields	High correlation
`min_bank` is highly correlated with `in_transit_qty` and 7 other fields	High correlation
`perf_6_month_avg` is highly correlated with `perf_12_month_avg`	High correlation
`perf_12_month_avg` is highly correlated with `perf_6_month_avg`	High correlation
`forecast_3_month` is highly correlated with `forecast_6_month` and 3 other fields	High correlation
`forecast_6_month` is highly correlated with `forecast_3_month` and 5 other fields	High correlation
`forecast_9_month` is highly correlated with `forecast_3_month` and 5 other fields	High correlation
`sales_1_month` is highly correlated with `forecast_3_month` and 6 other fields	High correlation
`sales_3_month` is highly correlated with `forecast_3_month` and 6 other fields	High correlation
`sales_6_month` is highly correlated with `forecast_6_month` and 5 other fields	High correlation
`sales_9_month` is highly correlated with `forecast_6_month` and 5 other fields	High correlation
`min_bank` is highly correlated with `sales_1_month` and 3 other fields	High correlation
`perf_6_month_avg` is highly correlated with `perf_12_month_avg`	High correlation
`perf_12_month_avg` is highly correlated with `perf_6_month_avg`	High correlation
`lead_time` is highly correlated with `perf_6_month_avg` and 1 other fields	High correlation
`in_transit_qty` is highly correlated with `forecast_3_month` and 7 other fields	High correlation
`forecast_3_month` is highly correlated with `in_transit_qty` and 7 other fields	High correlation
`forecast_6_month` is highly correlated with `in_transit_qty` and 7 other fields	High correlation
`forecast_9_month` is highly correlated with `in_transit_qty` and 7 other fields	High correlation
`sales_1_month` is highly correlated with `in_transit_qty` and 7 other fields	High correlation
`sales_3_month` is highly correlated with `in_transit_qty` and 7 other fields	High correlation
`sales_6_month` is highly correlated with `in_transit_qty` and 7 other fields	High correlation
`sales_9_month` is highly correlated with `in_transit_qty` and 7 other fields	High correlation
`min_bank` is highly correlated with `in_transit_qty` and 7 other fields	High correlation
`perf_6_month_avg` is highly correlated with `lead_time` and 1 other fields	High correlation
`perf_12_month_avg` is highly correlated with `lead_time` and 1 other fields	High correlation
`national_inv` is highly skewed (γ1 = 26.21876141)	Skewed
`pieces_past_due` is highly skewed (γ1 = 25.47929635)	Skewed
`sku` is uniformly distributed	Uniform
`sku` has unique values	Unique
`national_inv` has 5996 (10.2%) zeros	Zeros
`in_transit_qty` has 47312 (80.3%) zeros	Zeros
`forecast_3_month` has 34863 (59.2%) zeros	Zeros
`forecast_6_month` has 31574 (53.6%) zeros	Zeros
`forecast_9_month` has 29856 (50.7%) zeros	Zeros
`sales_1_month` has 30495 (51.8%) zeros	Zeros
`sales_3_month` has 23658 (40.2%) zeros	Zeros
`sales_6_month` has 20066 (34.1%) zeros	Zeros
`sales_9_month` has 18134 (30.8%) zeros	Zeros
`min_bank` has 30846 (52.4%) zeros	Zeros
`pieces_past_due` has 57335 (97.3%) zeros	Zeros
`perf_6_month_avg` has 1600 (2.7%) zeros	Zeros
`perf_12_month_avg` has 1232 (2.1%) zeros	Zeros
`local_bo_qty` has 57337 (97.3%) zeros	Zeros

Reproduction

Analysis started	2021-10-21 16:04:10.444487
Analysis finished	2021-10-21 16:04:55.477836
Duration	45.03 seconds
Software version	pandas-profiling v3.1.0
Download configuration	config.json

sku
Real number (ℝ_≥0)

UNIFORM
UNIQUE

Distinct	58919
Distinct (%)	100.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	42053.60125

Minimum	2
Maximum	84171
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	460.4 KiB

Quantile statistics

Minimum	2
5-th percentile	4186.9
Q1	21068.5
median	41948
Q3	63047
95-th percentile	80009.1
Maximum	84171
Range	84169
Interquartile range (IQR)	41978.5

Descriptive statistics

Standard deviation	24301.05717
Coefficient of variation (CV)	0.5778591239
Kurtosis	-1.197242328
Mean	42053.60125
Median Absolute Deviation (MAD)	20993
Skewness	0.004193389048
Sum	2477756132
Variance	590541379.8
Monotonicity	Strictly increasing

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
6141	1	< 0.1%
39430	1	< 0.1%
35332	1	< 0.1%
45571	1	< 0.1%
82429	1	< 0.1%
70135	1	< 0.1%
66037	1	< 0.1%
68084	1	< 0.1%
78323	1	< 0.1%
80370	1	< 0.1%
Other values (58909)	58909	> 99.9%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
2	1	< 0.1%
5	1	< 0.1%
7	1	< 0.1%
9	1	< 0.1%
10	1	< 0.1%
11	1	< 0.1%
16	1	< 0.1%
19	1	< 0.1%
20	1	< 0.1%
22	1	< 0.1%

Value	Count	Frequency (%)
84171	1	< 0.1%
84169	1	< 0.1%
84167	1	< 0.1%
84166	1	< 0.1%
84165	1	< 0.1%
84164	1	< 0.1%
84163	1	< 0.1%
84162	1	< 0.1%
84161	1	< 0.1%
84160	1	< 0.1%

national_inv
Real number (ℝ)

SKEWED
ZEROS

Distinct	2492
Distinct (%)	4.2%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	199.4039274

Minimum	-401
Maximum	75813
Zeros	5996
Zeros (%)	10.2%
Negative	713
Negative (%)	1.2%
Memory size	460.4 KiB

Quantile statistics

Minimum	-401
5-th percentile	0
Q1	3
median	11
Q3	54
95-th percentile	586
Maximum	75813
Range	76214
Interquartile range (IQR)	51

Descriptive statistics

Standard deviation	1529.148278
Coefficient of variation (CV)	7.668596591
Kurtosis	946.0195874
Mean	199.4039274
Median Absolute Deviation (MAD)	10
Skewness	26.21876141
Sum	11748680
Variance	2338294.457
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	5996	10.2%
2	4077	6.9%
3	3413	5.8%
1	2702	4.6%
4	2579	4.4%
5	2117	3.6%
6	1854	3.1%
7	1636	2.8%
10	1632	2.8%
8	1429	2.4%
Other values (2482)	31484	53.4%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
-401	1	< 0.1%
-213	1	< 0.1%
-152	2	< 0.1%
-126	1	< 0.1%
-120	1	< 0.1%
-102	1	< 0.1%
-100	2	< 0.1%
-98	1	< 0.1%
-93	1	< 0.1%
-89	2	< 0.1%

Value	Count	Frequency (%)
75813	1	< 0.1%
75254	1	< 0.1%
73148	1	< 0.1%
73128	1	< 0.1%
73066	1	< 0.1%
69500	1	< 0.1%
66712	1	< 0.1%
66314	1	< 0.1%
54344	1	< 0.1%
53785	1	< 0.1%

lead_time
Real number (ℝ_≥0)

HIGH CORRELATION

Distinct	27
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	6.915697822

Minimum	0
Maximum	28
Zeros	456
Zeros (%)	0.8%
Negative	0
Negative (%)	0.0%
Memory size	460.4 KiB

Quantile statistics

Minimum	0
5-th percentile	2
Q1	4
median	8
Q3	8
95-th percentile	12
Maximum	28
Range	28
Interquartile range (IQR)	4

Descriptive statistics

Standard deviation	3.522994714
Coefficient of variation (CV)	0.5094199897
Kurtosis	-0.4717713477
Mean	6.915697822
Median Absolute Deviation (MAD)	1
Skewness	-0.01686135996
Sum	407466
Variance	12.41149175
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=27)

Value	Count	Frequency (%)
8	25652	43.5%
2	13525	23.0%
12	7345	12.5%
4	4616	7.8%
9	4472	7.6%
3	679	1.2%
10	522	0.9%
0	456	0.8%
14	381	0.6%
16	330	0.6%
Other values (17)	941	1.6%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	456	0.8%
1	1	< 0.1%
2	13525	23.0%
3	679	1.2%
4	4616	7.8%
5	186	0.3%
6	190	0.3%
7	5	< 0.1%
8	25652	43.5%
9	4472	7.6%

Value	Count	Frequency (%)
28	4	< 0.1%
26	2	< 0.1%
25	1	< 0.1%
24	8	< 0.1%
22	6	< 0.1%
21	3	< 0.1%
20	24	< 0.1%
19	1	< 0.1%
18	6	< 0.1%
17	130	0.2%

in_transit_qty
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct	798
Distinct (%)	1.4%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	17.14075256

Minimum	0
Maximum	3872
Zeros	47312
Zeros (%)	80.3%
Negative	0
Negative (%)	0.0%
Memory size	460.4 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	0
Q3	0
95-th percentile	55
Maximum	3872
Range	3872
Interquartile range (IQR)	0

Descriptive statistics

Standard deviation	117.7503867
Coefficient of variation (CV)	6.869615922
Kurtosis	320.4235556
Mean	17.14075256
Median Absolute Deviation (MAD)	0
Skewness	15.37658738
Sum	1009916
Variance	13865.15356
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	47312	80.3%
1	1350	2.3%
2	764	1.3%
3	619	1.1%
4	592	1.0%
5	428	0.7%
6	380	0.6%
8	323	0.5%
10	314	0.5%
7	295	0.5%
Other values (788)	6542	11.1%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	47312	80.3%
1	1350	2.3%
2	764	1.3%
3	619	1.1%
4	592	1.0%
5	428	0.7%
6	380	0.6%
7	295	0.5%
8	323	0.5%
9	217	0.4%

Value	Count	Frequency (%)
3872	1	< 0.1%
3732	1	< 0.1%
3728	1	< 0.1%
3715	1	< 0.1%
3706	1	< 0.1%
3695	1	< 0.1%
3500	1	< 0.1%
3371	1	< 0.1%
3201	1	< 0.1%
3185	1	< 0.1%

forecast_3_month
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct	1536
Distinct (%)	2.6%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	87.25288956

Minimum	0
Maximum	15600
Zeros	34863
Zeros (%)	59.2%
Negative	0
Negative (%)	0.0%
Memory size	460.4 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	0
Q3	12
95-th percentile	335
Maximum	15600
Range	15600
Interquartile range (IQR)	12

Descriptive statistics

Standard deviation	497.8202309
Coefficient of variation (CV)	5.705487044
Kurtosis	253.2248987
Mean	87.25288956
Median Absolute Deviation (MAD)	0
Skewness	13.55471877
Sum	5140853
Variance	247824.9823
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	34863	59.2%
1	1354	2.3%
2	1243	2.1%
5	1056	1.8%
4	962	1.6%
3	885	1.5%
10	774	1.3%
6	743	1.3%
8	611	1.0%
12	603	1.0%
Other values (1526)	15825	26.9%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	34863	59.2%
1	1354	2.3%
2	1243	2.1%
3	885	1.5%
4	962	1.6%
5	1056	1.8%
6	743	1.3%
7	457	0.8%
8	611	1.0%
9	374	0.6%

Value	Count	Frequency (%)
15600	1	< 0.1%
15552	1	< 0.1%
14730	1	< 0.1%
14350	1	< 0.1%
14000	1	< 0.1%
13608	1	< 0.1%
13320	1	< 0.1%
13140	1	< 0.1%
12630	1	< 0.1%
12543	1	< 0.1%

forecast_6_month
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct	2090
Distinct (%)	3.5%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	162.1785672

Minimum	0
Maximum	29200
Zeros	31574
Zeros (%)	53.6%
Negative	0
Negative (%)	0.0%
Memory size	460.4 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	0
Q3	26
95-th percentile	606
Maximum	29200
Range	29200
Interquartile range (IQR)	26

Descriptive statistics

Standard deviation	913.3398768
Coefficient of variation (CV)	5.631692847
Kurtosis	249.2752524
Mean	162.1785672
Median Absolute Deviation (MAD)	0
Skewness	13.43519199
Sum	9555399
Variance	834189.7305
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	31574	53.6%
1	1109	1.9%
2	1077	1.8%
3	986	1.7%
4	924	1.6%
5	864	1.5%
6	766	1.3%
10	757	1.3%
8	681	1.2%
7	640	1.1%
Other values (2080)	19541	33.2%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	31574	53.6%
1	1109	1.9%
2	1077	1.8%
3	986	1.7%
4	924	1.6%
5	864	1.5%
6	766	1.3%
7	640	1.1%
8	681	1.2%
9	406	0.7%

Value	Count	Frequency (%)
29200	1	< 0.1%
29000	1	< 0.1%
26250	1	< 0.1%
25930	1	< 0.1%
25620	1	< 0.1%
25500	1	< 0.1%
25200	1	< 0.1%
24472	1	< 0.1%
22212	1	< 0.1%
22200	1	< 0.1%

forecast_9_month
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct	2522
Distinct (%)	4.3%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	237.7437838

Minimum	0
Maximum	43000
Zeros	29856
Zeros (%)	50.7%
Negative	0
Negative (%)	0.0%
Memory size	460.4 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	0
Q3	40
95-th percentile	900
Maximum	43000
Range	43000
Interquartile range (IQR)	40

Descriptive statistics

Standard deviation	1345.784311
Coefficient of variation (CV)	5.660649836
Kurtosis	250.786079
Mean	237.7437838
Median Absolute Deviation (MAD)	0
Skewness	13.54096418
Sum	14007626
Variance	1811135.412
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	29856	50.7%
1	1003	1.7%
2	994	1.7%
4	893	1.5%
3	889	1.5%
5	844	1.4%
6	809	1.4%
10	793	1.3%
8	686	1.2%
12	641	1.1%
Other values (2512)	21511	36.5%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	29856	50.7%
1	1003	1.7%
2	994	1.7%
3	889	1.5%
4	893	1.5%
5	844	1.4%
6	809	1.4%
7	557	0.9%
8	686	1.2%
9	429	0.7%

Value	Count	Frequency (%)
43000	1	< 0.1%
40720	1	< 0.1%
38820	1	< 0.1%
38580	1	< 0.1%
36000	1	< 0.1%
35730	1	< 0.1%
35700	1	< 0.1%
34200	1	< 0.1%
33421	1	< 0.1%
33408	1	< 0.1%

sales_1_month
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct	961
Distinct (%)	1.6%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	25.50520206

Minimum	0
Maximum	4934
Zeros	30495
Zeros (%)	51.8%
Negative	0
Negative (%)	0.0%
Memory size	460.4 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	0
Q3	6
95-th percentile	101
Maximum	4934
Range	4934
Interquartile range (IQR)	6

Descriptive statistics

Standard deviation	136.6048481
Coefficient of variation (CV)	5.355960238
Kurtosis	280.0051028
Mean	25.50520206
Median Absolute Deviation (MAD)	0
Skewness	13.88048916
Sum	1502741
Variance	18660.88452
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	30495	51.8%
1	5316	9.0%
2	3146	5.3%
3	2191	3.7%
4	1624	2.8%
5	1343	2.3%
6	1046	1.8%
7	868	1.5%
8	691	1.2%
9	610	1.0%
Other values (951)	11589	19.7%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	30495	51.8%
1	5316	9.0%
2	3146	5.3%
3	2191	3.7%
4	1624	2.8%
5	1343	2.3%
6	1046	1.8%
7	868	1.5%
8	691	1.2%
9	610	1.0%

Value	Count	Frequency (%)
4934	1	< 0.1%
4627	1	< 0.1%
4326	1	< 0.1%
4297	1	< 0.1%
4019	1	< 0.1%
3926	1	< 0.1%
3817	1	< 0.1%
3685	1	< 0.1%
3558	1	< 0.1%
3511	1	< 0.1%

sales_3_month
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct	1804
Distinct (%)	3.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	82.25299139

Minimum	0
Maximum	13554
Zeros	23658
Zeros (%)	40.2%
Negative	0
Negative (%)	0.0%
Memory size	460.4 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	2
Q3	18
95-th percentile	325
Maximum	13554
Range	13554
Interquartile range (IQR)	18

Descriptive statistics

Standard deviation	430.1854963
Coefficient of variation (CV)	5.230028586
Kurtosis	223.8563959
Mean	82.25299139
Median Absolute Deviation (MAD)	2
Skewness	12.66619534
Sum	4846264
Variance	185059.5612
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	23658	40.2%
1	4518	7.7%
2	2997	5.1%
3	2049	3.5%
4	1625	2.8%
5	1389	2.4%
6	1152	2.0%
7	950	1.6%
8	877	1.5%
9	760	1.3%
Other values (1794)	18944	32.2%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	23658	40.2%
1	4518	7.7%
2	2997	5.1%
3	2049	3.5%
4	1625	2.8%
5	1389	2.4%
6	1152	2.0%
7	950	1.6%
8	877	1.5%
9	760	1.3%

Value	Count	Frequency (%)
13554	1	< 0.1%
12703	1	< 0.1%
12392	1	< 0.1%
12272	1	< 0.1%
12209	1	< 0.1%
11180	1	< 0.1%
11127	1	< 0.1%
10557	1	< 0.1%
10510	1	< 0.1%
10297	1	< 0.1%

sales_6_month
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct	2528
Distinct (%)	4.3%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	163.3491403

Minimum	0
Maximum	26299
Zeros	20066
Zeros (%)	34.1%
Negative	0
Negative (%)	0.0%
Memory size	460.4 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	4
Q3	35
95-th percentile	644.1
Maximum	26299
Range	26299
Interquartile range (IQR)	35

Descriptive statistics

Standard deviation	860.7644959
Coefficient of variation (CV)	5.269476742
Kurtosis	228.0201025
Mean	163.3491403
Median Absolute Deviation (MAD)	4
Skewness	12.82974373
Sum	9624368
Variance	740915.5173
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	20066	34.1%
1	4116	7.0%
2	2757	4.7%
3	1899	3.2%
4	1567	2.7%
5	1268	2.2%
6	1124	1.9%
8	881	1.5%
7	867	1.5%
9	726	1.2%
Other values (2518)	23648	40.1%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	20066	34.1%
1	4116	7.0%
2	2757	4.7%
3	1899	3.2%
4	1567	2.7%
5	1268	2.2%
6	1124	1.9%
7	867	1.5%
8	881	1.5%
9	726	1.2%

Value	Count	Frequency (%)
26299	1	< 0.1%
25179	1	< 0.1%
23968	1	< 0.1%
23872	1	< 0.1%
23560	1	< 0.1%
23275	1	< 0.1%
22080	1	< 0.1%
21945	1	< 0.1%
21610	1	< 0.1%
21442	1	< 0.1%

sales_9_month
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct	3062
Distinct (%)	5.2%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	248.471936

Minimum	0
Maximum	42656
Zeros	18134
Zeros (%)	30.8%
Negative	0
Negative (%)	0.0%
Memory size	460.4 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	6
Q3	52
95-th percentile	972
Maximum	42656
Range	42656
Interquartile range (IQR)	52

Descriptive statistics

Standard deviation	1321.245573
Coefficient of variation (CV)	5.317484117
Kurtosis	255.5284637
Mean	248.471936
Median Absolute Deviation (MAD)	6
Skewness	13.33812818
Sum	14639718
Variance	1745689.865
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	18134	30.8%
1	3823	6.5%
2	2615	4.4%
3	1878	3.2%
4	1484	2.5%
5	1265	2.1%
6	1097	1.9%
7	887	1.5%
8	777	1.3%
9	729	1.2%
Other values (3052)	26230	44.5%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	18134	30.8%
1	3823	6.5%
2	2615	4.4%
3	1878	3.2%
4	1484	2.5%
5	1265	2.1%
6	1097	1.9%
7	887	1.5%
8	777	1.3%
9	729	1.2%

Value	Count	Frequency (%)
42656	1	< 0.1%
42526	1	< 0.1%
41111	1	< 0.1%
39066	1	< 0.1%
38804	1	< 0.1%
38194	1	< 0.1%
37472	1	< 0.1%
37448	1	< 0.1%
35976	1	< 0.1%
35078	1	< 0.1%

min_bank
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct	917
Distinct (%)	1.6%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	26.15448327

Minimum	0
Maximum	3390
Zeros	30846
Zeros (%)	52.4%
Negative	0
Negative (%)	0.0%
Memory size	460.4 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	0
Q3	3
95-th percentile	115
Maximum	3390
Range	3390
Interquartile range (IQR)	3

Descriptive statistics

Standard deviation	129.5775772
Coefficient of variation (CV)	4.954316086
Kurtosis	195.1081789
Mean	26.15448327
Median Absolute Deviation (MAD)	0
Skewness	12.01563522
Sum	1540996
Variance	16790.34852
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	30846	52.4%
1	8446	14.3%
2	3778	6.4%
3	1257	2.1%
4	850	1.4%
5	603	1.0%
6	437	0.7%
7	343	0.6%
15	285	0.5%
8	273	0.5%
Other values (907)	11801	20.0%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	30846	52.4%
1	8446	14.3%
2	3778	6.4%
3	1257	2.1%
4	850	1.4%
5	603	1.0%
6	437	0.7%
7	343	0.6%
8	273	0.5%
9	210	0.4%

Value	Count	Frequency (%)
3390	1	< 0.1%
3303	1	< 0.1%
3159	1	< 0.1%
3105	1	< 0.1%
3083	1	< 0.1%
3045	2	< 0.1%
3023	1	< 0.1%
3021	1	< 0.1%
3005	1	< 0.1%
2996	1	< 0.1%

potential_issue
Categorical

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	460.4 KiB

0	58858
1	61

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	58858	99.9%
1	61	0.1%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	58858	99.9%
1	61	0.1%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

pieces_past_due
Real number (ℝ_≥0)

SKEWED
ZEROS

Distinct	171
Distinct (%)	0.3%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	0.9727252669

Minimum	0
Maximum	638
Zeros	57335
Zeros (%)	97.3%
Negative	0
Negative (%)	0.0%
Memory size	460.4 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	0
Q3	0
95-th percentile	0
Maximum	638
Range	638
Interquartile range (IQR)	0

Descriptive statistics

Standard deviation	13.79268948
Coefficient of variation (CV)	14.17942964
Kurtosis	796.3752099
Mean	0.9727252669
Median Absolute Deviation (MAD)	0
Skewness	25.47929635
Sum	57312
Variance	190.2382832
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	57335	97.3%
1	233	0.4%
2	149	0.3%
4	88	0.1%
3	72	0.1%
5	65	0.1%
12	61	0.1%
6	53	0.1%
10	45	0.1%
8	43	0.1%
Other values (161)	775	1.3%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	57335	97.3%
1	233	0.4%
2	149	0.3%
3	72	0.1%
4	88	0.1%
5	65	0.1%
6	53	0.1%
7	39	0.1%
8	43	0.1%
9	26	< 0.1%

Value	Count	Frequency (%)
638	1	< 0.1%
600	2	< 0.1%
544	1	< 0.1%
540	2	< 0.1%
520	1	< 0.1%
500	3	< 0.1%
464	1	< 0.1%
455	1	< 0.1%
450	1	< 0.1%
446	1	< 0.1%

perf_6_month_avg
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct	101
Distinct (%)	0.2%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	0.7717668324

Minimum	0
Maximum	1
Zeros	1600
Zeros (%)	2.7%
Negative	0
Negative (%)	0.0%
Memory size	460.4 KiB

Quantile statistics

Minimum	0
5-th percentile	0.19
Q1	0.69
median	0.84
Q3	0.97
95-th percentile	1
Maximum	1
Range	1
Interquartile range (IQR)	0.28

Descriptive statistics

Standard deviation	0.2449000802
Coefficient of variation (CV)	0.3173239247
Kurtosis	1.861181803
Mean	0.7717668324
Median Absolute Deviation (MAD)	0.13
Skewness	-1.504102324
Sum	45471.73
Variance	0.0599760493
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0.99	5137	8.7%
1	4704	8.0%
0.73	3963	6.7%
0.98	3150	5.3%
0.97	2374	4.0%
0.78	1782	3.0%
0.82	1601	2.7%
0	1600	2.7%
0.95	1553	2.6%
0.96	1479	2.5%
Other values (91)	31576	53.6%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	1600	2.7%
0.01	15	< 0.1%
0.02	58	0.1%
0.03	30	0.1%
0.04	27	< 0.1%
0.05	79	0.1%
0.06	44	0.1%
0.07	99	0.2%
0.08	80	0.1%
0.09	65	0.1%

Value	Count	Frequency (%)
1	4704	8.0%
0.99	5137	8.7%
0.98	3150	5.3%
0.97	2374	4.0%
0.96	1479	2.5%
0.95	1553	2.6%
0.94	1370	2.3%
0.93	1236	2.1%
0.92	868	1.5%
0.91	1147	1.9%

perf_12_month_avg
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct	101
Distinct (%)	0.2%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	0.7685442726

Minimum	0
Maximum	1
Zeros	1232
Zeros (%)	2.1%
Negative	0
Negative (%)	0.0%
Memory size	460.4 KiB

Quantile statistics

Minimum	0
5-th percentile	0.23
Q1	0.68
median	0.82
Q3	0.95
95-th percentile	0.99
Maximum	1
Range	1
Interquartile range (IQR)	0.27

Descriptive statistics

Standard deviation	0.2351967542
Coefficient of variation (CV)	0.3060288946
Kurtosis	2.002128514
Mean	0.7685442726
Median Absolute Deviation (MAD)	0.13
Skewness	-1.527267546
Sum	45281.86
Variance	0.05531751319
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0.99	4707	8.0%
0.78	4160	7.1%
0.98	3442	5.8%
0.97	2471	4.2%
0.96	2289	3.9%
0.66	1979	3.4%
0.9	1752	3.0%
0.95	1684	2.9%
1	1540	2.6%
0.79	1493	2.5%
Other values (91)	33402	56.7%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	1232	2.1%
0.01	91	0.2%
0.02	25	< 0.1%
0.03	28	< 0.1%
0.04	42	0.1%
0.05	34	0.1%
0.06	37	0.1%
0.07	55	0.1%
0.08	56	0.1%
0.09	100	0.2%

Value	Count	Frequency (%)
1	1540	2.6%
0.99	4707	8.0%
0.98	3442	5.8%
0.97	2471	4.2%
0.96	2289	3.9%
0.95	1684	2.9%
0.94	1424	2.4%
0.93	1207	2.0%
0.92	1129	1.9%
0.91	1129	1.9%

local_bo_qty
Real number (ℝ_≥0)

ZEROS

Distinct	92
Distinct (%)	0.2%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	0.2821161255

Minimum	0
Maximum	127
Zeros	57337
Zeros (%)	97.3%
Negative	0
Negative (%)	0.0%
Memory size	460.4 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	0
Q3	0
95-th percentile	0
Maximum	127
Range	127
Interquartile range (IQR)	0

Descriptive statistics

Standard deviation	3.333715762
Coefficient of variation (CV)	11.81682102
Kurtosis	435.8098306
Mean	0.2821161255
Median Absolute Deviation (MAD)	0
Skewness	18.94450855
Sum	16622
Variance	11.11366078
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	57337	97.3%
1	475	0.8%
2	204	0.3%
3	143	0.2%
4	110	0.2%
5	65	0.1%
6	58	0.1%
7	44	0.1%
8	37	0.1%
10	30	0.1%
Other values (82)	416	0.7%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	57337	97.3%
1	475	0.8%
2	204	0.3%
3	143	0.2%
4	110	0.2%
5	65	0.1%
6	58	0.1%
7	44	0.1%
8	37	0.1%
9	22	< 0.1%

Value	Count	Frequency (%)
127	1	< 0.1%
119	1	< 0.1%
102	1	< 0.1%
100	4	< 0.1%
98	1	< 0.1%
97	1	< 0.1%
96	1	< 0.1%
93	1	< 0.1%
92	1	< 0.1%
91	1	< 0.1%

deck_risk
Categorical

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	460.4 KiB

0	48287
1	10632

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	48287	82.0%
1	10632	18.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	48287	82.0%
1	10632	18.0%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

oe_constraint
Categorical

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	460.4 KiB

0	58908
1	11

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	58908	> 99.9%
1	11	< 0.1%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	58908	> 99.9%
1	11	< 0.1%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

ppap_risk
Categorical

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	460.4 KiB

0	51794
1	7125

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	51794	87.9%
1	7125	12.1%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	51794	87.9%
1	7125	12.1%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

stop_auto_buy
Categorical

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	460.4 KiB

1	57870
0	1049

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1
2nd row	1
3rd row	1
4th row	1
5th row	1

Common Values

Value	Count	Frequency (%)
1	57870	98.2%
0	1049	1.8%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
1	57870	98.2%
0	1049	1.8%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

rev_stop
Categorical

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	460.4 KiB

0	58904
1	15

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	58904	> 99.9%
1	15	< 0.1%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	58904	> 99.9%
1	15	< 0.1%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

went_on_backorder
Categorical

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	460.4 KiB

0	49624
1	9295

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	49624	84.2%
1	9295	15.8%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	49624	84.2%
1	9295	15.8%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.

Cramér's V (φc)

Cramér's V is an association measure for nominal random variables. The coefficient ranges from 0 to 1, with 0 indicating independence and 1 indicating perfect association. The empirical estimators used for Cramér's V have been proved to be biased, even for large samples. We use a bias-corrected measure that has been proposed by Bergsma in 2013 that can be found here.

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

Count
Matrix

A simple visualization of nullity by column.

Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

First rows

	sku	national_inv	lead_time	in_transit_qty	forecast_3_month	forecast_6_month	forecast_9_month	sales_1_month	sales_3_month	sales_6_month	sales_9_month	min_bank	perf_6_month_avg	perf_12_month_avg	deck_risk	ppap_risk	stop_auto_buy
0	2	4	2	0	0	0	0	0	0	0	0	0	0.18	0.31	1	0	1
1	5	2	16	0	0	0	0	0	0	0	0	1	0.31	0.40	0	0	1
2	7	4	4	0	0	0	0	0	0	0	0	0	0.73	0.78	0	0	1
3	9	0	9	0	1	1	1	0	0	0	0	0	0.86	0.69	0	0	1
4	10	300	8	0	0	0	0	0	40	100	122	7	0.00	0.00	0	0	1
5	11	1	12	0	0	0	0	0	1	2	2	2	0.77	0.73	1	0	1
6	16	9635	8	26	0	0	0	88	267	538	875	97	0.12	0.12	0	0	1
7	19	4	8	0	0	0	0	1	7	7	9	2	0.62	0.62	1	1	1
8	20	22	4	16	18	36	54	1	20	36	51	0	0.73	0.78	0	0	1
9	22	218	9	113	218	323	353	61	147	377	558	62	0.85	0.82	0	0	1

Last rows

	sku	national_inv	lead_time	forecast_3_month	forecast_6_month	forecast_9_month	sales_1_month	sales_3_month	sales_6_month	sales_9_month	min_bank	pieces_past_due	perf_6_month_avg	perf_12_month_avg	deck_risk	ppap_risk	stop_auto_buy	went_on_backorder
58909	84160	4	2	5	5	5	2	6	6	6	1	0	0.97	0.98	1	1	1	0
58910	84161	4	8	0	0	0	0	0	1	1	0	0	0.99	0.96	0	0	1	0
58911	84162	79	2	0	0	0	6	11	16	23	0	0	1.00	0.95	0	0	1	0
58912	84163	2	2	0	0	0	0	0	0	0	0	0	0.42	0.36	1	1	1	0
58913	84164	4	2	24	48	72	16	29	46	69	0	0	0.98	0.97	0	0	1	1
58914	84165	11	8	0	0	0	2	6	17	26	6	0	0.54	0.64	1	0	1	0
58915	84166	0	8	4	5	7	2	3	4	5	0	0	0.76	0.77	0	0	1	1
58916	84167	0	2	1	1	1	0	0	0	0	0	0	0.09	0.06	0	0	1	1
58917	84169	6	4	0	0	0	0	0	0	0	0	0	0.77	0.80	1	0	1	0
58918	84171	0	12	50	50	50	0	0	0	0	0	50	0.63	0.63	1	0	1	0

Overview

Variables

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Interactions

Correlations

Spearman's ρ

Pearson's r

Kendall's τ

Cramér's V (φc)

Phik (φk)

Missing values